Tip Based Automated Nanomanipulation using Scanning Probe Microscopy

The promise to build structures atom by atom that would lead to devices or materials with tuned properties that surpass any material we encounter in the macroscale world inspires more researchers everyday to study nanotechnology. As a direct result of this interest in nanotechnology, manipulation systems with nano or sub-nano scale precision are required to position or pattern matter in smaller scales to study it. However, this manipulation task is not straightforward due to small scale physics, which reduces the effect of weight and inertia, the dominant forces in macroscale, and promotes other forces such as adhesion or electrostatic interactions. Hence, to understand nanoscale physics, the first step to take is to model and characterize the underlying principles. In this context, scanning probe microscopes (SPMs) are suitable tools for experimenting on nanoscale physics, in addition to being good candidates as nanomanipulation systems due to their ability to locally interact with the substrate using the end-effector that they utilize on the order of a few nanometers or below. On the other hand, using SPMs for nanomanipulation has drawbacks as well. Since they utilize a single end-effector to interact with the substrate, the manipulation process is serial hence slow with low throughput. Furthermore, having no real-time visual feedback and the non-linearity of the actuators decrease the precision and the repeatability of the positioning, hence decreasing the reliability of the manipulation. In order to consider SPMs as viable nanomanipulation tools, these challenges of speed and reliability should first be tackled by utilizing smarter algorithms and mechanisms.

In this work, we demonstrate two case studies that are used for tackling the speed and reliability challenges of nanomanipulation. As the first case study, an AFM is utilized to position nanoparticles. In the AFM based mechanical contact manipulation of nanoparticles, we demonstrate automated control to increase speed and reliability. In order to achieve the automation, we present models to investigate the physics of nanoparticle manipulation using an AFM cantilever, and use these models to investigate the effect of cantilever selection to manipulation success. We demonstrate particle detection using line-scans and a contact loss detection algorithm using cantilever normal deflection data to decrease the number of images taken during manipulation. We also demonstrate through experimental results that it is possible to push and pull particles on a flat surface into defined patterns autonomously, using an AFM probe tip, and with an error less than the particle diameter, and with success rates as high as 87%.

Moreover, an STM is utilized to manipulate surfaces using electrical pulses and high electric fields as a second case study of this thesis. During the STM based electrical non-contact manipulation, utilizing conductive AFM probes as STM end-effectors as a step towards a multiple probe approach is suggested to improve the speed and throughput of the STM manipulation. STM imaging of surfaces using STM tips and conductive AFM probes are demonstrated and algorithms for STM based electrical manipulation of surfaces is presented and experimentally verified. Furthermore, models for STM operation and manipulation using STM tips and AFM probes as end-effectors are developed and the effects of several design parameters on STM based imaging and manipulation that utilizes AFM probes and STM tips are investigated. In addition, a faster and more flexible controller is designed and implemented which allows instant switching between AFM and STM modes, when conductive AFM probes are utilized.